Blotchy return period wind hazard maps

[richsdixon]

Hi - like another poster I am looking at Atlantic wind hazard - I've started running the tool (I've included the .ini file below) but I'm finding the return period maps are quite "blotchy" and - as suggested in another "issue" - the hazard is pretty low, however I don't get the smoothness of output that the other person is getting.

Is anyone able to offer any advice as to why this is so "blotchy"? My only guess is that it's a function of running only 1000 years of simulation: however in those 1000 years I would hope that I'm still seeing a return period well above 30 m/s in most places for the 50-year wind hazard. Thanks in advance for any help here.

[Actions]
; TCRM modules to execute
DataProcess=True
ExecuteStat=True
ExecuteTrackGenerator=True
ExecuteWindfield=True
ExecuteHazard=True
CreateDatabase=True
PlotHazard=True

PlotData=False

ExecuteEvaluate=False
DownloadData=False

[DataProcess]
InputFile=ibtracs.NA.list.v04r00.csv
Source=IBTRACS
StartSeason=1970
FilterSeasons=True

[Region]
; Domain for windfield and hazard calculation
gridLimit={'xMin':275.0,'xMax':285.0,'yMin':24.0,'yMax':34.0}
gridSpace={'x':1.0,'y':1.0}
gridInc={'x':1.0,'y':0.5}
LocalityID=250913860
LocalityName=Florida, USA

[StatInterface]
kdeType=gau
kde2DType=Gaussian
kdeStep=0.2

[TrackGenerator]
NumSimulations=1000
YearsPerSimulation=1
SeasonSeed=403943
TrackSeed=89333

[WindfieldInterface]
;TrackPath=./output/florida6/tracks
Margin=5.0
Resolution=0.02
Source=TCRM
profileType=holland
windFieldType=kepert

[Hazard]
; Years to calculate return period wind speeds
InputPath=./output/florida6/windfield
;Resolution=0.05
Years=2,5,10,50
MinimumRecords=10
CalculateCI=False

[Input]
#LocationFile = input/USZipShapefile.shp
LocationFile = input/stationlist.shp
landmask = input/landmask.nc
mslpfile = MSLP/slp.day.ltm.nc
datasets = IBTRACS,LTMSLP
MSLPGrid=1,2,3,4,12

[Output]
Path=./output/florida6

[Logging]
LogFile=./output/florida6/log/florida6.log
LogLevel=INFO
Verbose=False

[Process]
ExcludePastProcessed=True
DatFile=./output/florida6/process/dat/florida6.dat

[RMW]
GetRMWDistFromInputData=False
mean=50.0
sigma=0.6

[TCRM]
; Output track files settings
Columns=index,age,lon,lat,speed,bearing,pressure,penv,rmax
FieldDelimiter=,
NumberOfHeadingLines=1
SpeedUnits=kph
PressureUnits=hPa

[IBTRACS]
; Input data file settings
; url = ftp://eclipse.ncdc.noaa.gov/pub/ibtracs/v03r10/wmo/csv/Allstorms.ibtracs_wmo.v03r10.csv.gz
;url = https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r00/access/csv/ibtracs.ALL.list.v04r00.csv
path = input
filename = ibtracs.NA.list.v04r00.csv
columns = tcserialno,season,num,skip,skip,skip,date,skip,lat,lon,skip,pressure
fielddelimiter = ,
numberofheadinglines = 2
pressureunits = hPa
lengthunits = km
dateformat = %Y-%m-%d %H:%M:%S
speedunits = mph

[LTMSLP]
; MSLP climatology file settings
URL = ftp://ftp.cdc.noaa.gov/Datasets/ncep.reanalysis.derived/surface/slp.day.1981-2010.ltm.nc
path = MSLP
filename = slp.day.ltm.nc

[wcarthur]

There is a 1 degree smoothing filter applied to the data before plotting (the underlying data in the hazard/hazard.nc file is unchanged). The smoothing filter propagates missing values. In the case of the example simulations, the likelihood of a grid point not recording a wind speed is moderate, leading to the blotchiness. We've implemented the filter to avoid

Solutions include increasing the Margin setting and increasing the number of simulations NumSimulations. Alternatively, you can comment out the firt three lines in the HazardMap.plot method in PlotInterface/maps.py

class HazardMap(FilledContourMapFigure):
    """
    A map for presenting return level data. 

    """
    def plot(self, data, xgrid, ygrid, title, lvls, cbarlab, map_kwargs):
        #dx = np.mean(np.diff(xgrid))
        #dmask = data.mask
        #data = ma.array(data, mask=dmask)
        self.add(data, xgrid, ygrid, title, lvls, cbarlab, map_kwargs)
        self.cmap = sns.light_palette("orange", as_cmap=True)
        super(HazardMap, self).plot()